{"id":"https://openalex.org/W3165963211","doi":"https://doi.org/10.1145/3447548.3467168","title":"Heterogeneous Temporal Graph Transformer","display_name":"Heterogeneous Temporal Graph Transformer","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3165963211","doi":"https://doi.org/10.1145/3447548.3467168","mag":"3165963211"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467168","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101916154","display_name":"Yujie Fan","orcid":"https://orcid.org/0000-0002-2635-9420"},"institutions":[{"id":"https://openalex.org/I58956616","display_name":"Case Western Reserve University","ror":"https://ror.org/051fd9666","country_code":"US","type":"education","lineage":["https://openalex.org/I58956616"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yujie Fan","raw_affiliation_strings":["Case Western Reserve University, Cleveland, OH, USA"],"affiliations":[{"raw_affiliation_string":"Case Western Reserve University, Cleveland, OH, USA","institution_ids":["https://openalex.org/I58956616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000740265","display_name":"Mingxuan Ju","orcid":"https://orcid.org/0000-0003-0519-7829"},"institutions":[{"id":"https://openalex.org/I58956616","display_name":"Case Western Reserve University","ror":"https://ror.org/051fd9666","country_code":"US","type":"education","lineage":["https://openalex.org/I58956616"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingxuan Ju","raw_affiliation_strings":["Case Western Reserve University, Cleveland, OH, USA"],"affiliations":[{"raw_affiliation_string":"Case Western Reserve University, Cleveland, OH, USA","institution_ids":["https://openalex.org/I58956616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110964699","display_name":"Shifu Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I58956616","display_name":"Case Western Reserve University","ror":"https://ror.org/051fd9666","country_code":"US","type":"education","lineage":["https://openalex.org/I58956616"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shifu Hou","raw_affiliation_strings":["Case Western Reserve University, Cleveland, OH, USA"],"affiliations":[{"raw_affiliation_string":"Case Western Reserve University, Cleveland, OH, USA","institution_ids":["https://openalex.org/I58956616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101586436","display_name":"Yanfang Ye","orcid":"https://orcid.org/0000-0001-8376-7239"},"institutions":[{"id":"https://openalex.org/I58956616","display_name":"Case Western Reserve University","ror":"https://ror.org/051fd9666","country_code":"US","type":"education","lineage":["https://openalex.org/I58956616"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanfang Ye","raw_affiliation_strings":["Case Western Reserve University, Cleveland, OH, USA"],"affiliations":[{"raw_affiliation_string":"Case Western Reserve University, Cleveland, OH, USA","institution_ids":["https://openalex.org/I58956616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046206064","display_name":"Wenqiang Wan","orcid":"https://orcid.org/0009-0001-6510-0171"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqiang Wan","raw_affiliation_strings":["Tencent, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100342699","display_name":"Kui Wang","orcid":"https://orcid.org/0009-0000-0821-1660"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kui Wang","raw_affiliation_strings":["Tencent, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111827604","display_name":"Yinming Mei","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinming Mei","raw_affiliation_strings":["Tencent, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000664704","display_name":"Qi Xiong","orcid":"https://orcid.org/0000-0001-8690-565X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Xiong","raw_affiliation_strings":["Tencent, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5101916154"],"corresponding_institution_ids":["https://openalex.org/I58956616"],"apc_list":null,"apc_paid":null,"fwci":5.1803,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.96355646,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2831","last_page":"2839"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9751999974250793,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8234379291534424},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.8167825937271118},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.653719961643219},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48864656686782837},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4074236750602722},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3559989929199219},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.11604833602905273}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8234379291534424},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.8167825937271118},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.653719961643219},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48864656686782837},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4074236750602722},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3559989929199219},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.11604833602905273}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3467168","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6892618907","display_name":null,"funder_award_id":"IIS-2027127, IIS-2040144, IIS-1951504, CNS-2034470, CNS-1940859, CNS-1814825, OAC-1940855 and ECCS-2026612","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W103340358","https://openalex.org/W2577741565","https://openalex.org/W2612186685","https://openalex.org/W2732916693","https://openalex.org/W2744097819","https://openalex.org/W2788503006","https://openalex.org/W2885070483","https://openalex.org/W2900275727","https://openalex.org/W2903871660","https://openalex.org/W2904449562","https://openalex.org/W2911286998","https://openalex.org/W2966270452","https://openalex.org/W2996451395","https://openalex.org/W3012562343","https://openalex.org/W3015285715","https://openalex.org/W3042914280","https://openalex.org/W3080203535","https://openalex.org/W3081469395","https://openalex.org/W3097237405","https://openalex.org/W3176588063"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W1966145327"],"abstract_inverted_index":{"The":[0],"explosive":[1],"growth":[2],"and":[3,30,42,58,75,103,114,141,177,188,247],"increasing":[4],"sophistication":[5],"of":[6,91,186,208,240],"Android":[7],"malware":[8,40,95,112,153],"call":[9],"for":[10,44,152,183,222],"new":[11],"defensive":[12],"techniques":[13],"to":[14,37,70,83,109,137,148,160,170,179,190,202],"protect":[15],"mobile":[16,249],"users":[17],"against":[18],"novel":[19,128],"threats.":[20],"To":[21,93],"address":[22],"this":[23,26],"challenge,":[24],"in":[25,156,218],"paper,":[27],"we":[28,53,77,97,125,164,194],"propose":[29,126],"develop":[31],"an":[32,219],"intelligent":[33],"system":[34],"named":[35],"Dr.Droid":[36],"jointly":[38,110],"model":[39,84,111,191],"propagation":[41,73,113],"evolution":[43,115],"their":[45],"detection":[46],"at":[47],"the":[48,62,85,100,146,162,200,214,230,238],"first":[49,54],"attempt.":[50],"In":[51],"Dr.Droid,":[52,241],"exploit":[55],"higher-level":[56],"semantic":[57],"social":[59],"relations":[60,68,87],"within":[61],"ecosystem":[63],"(e.g.,":[64,212],"app-market,":[65],"app-developer,":[66],"market-developer":[67],"etc.)":[69],"characterize":[71],"app":[72],"patterns;":[74],"then":[76],"present":[78],"a":[79,105,127,166,196,209],"structured":[80],"heterogeneous":[81,106,118,129,167,172],"graph":[82,108,131],"complex":[86],"among":[88],"different":[89,184],"types":[90,185],"entities.":[92],"capture":[94],"evolution,":[96],"further":[98],"consider":[99],"temporal":[101,107,122,130,142,192,197],"dependence":[102],"introduce":[104],"by":[116,242],"considering":[117],"spatial":[119,140,168],"dependencies":[120,143],"with":[121,244],"dimensions.":[123],"Afterwards,":[124],"transformer":[132,169,198],"framework":[133],"(denoted":[134],"as":[135],"HTGT)":[136],"integrate":[138],"both":[139],"while":[144],"preserving":[145],"heterogeneity":[147],"learn":[149,180],"node":[150,176,211],"representations":[151,182],"detection.":[154],"Specifically,":[155],"our":[157],"proposed":[158],"HTGT,":[159],"preserve":[161],"heterogeneity,":[163],"devise":[165],"derive":[171],"attentions":[173],"over":[174],"each":[175],"edge":[178],"dedicated":[181],"entities":[187],"relations;":[189],"dependencies,":[193],"design":[195],"into":[199],"HTGT":[201],"attentively":[203],"aggregate":[204],"its":[205],"historical":[206],"sequences":[207],"given":[210],"app);":[213],"two":[215],"transformers":[216],"work":[217],"iterative":[220],"manner":[221],"representation":[223],"learning.":[224],"Promising":[225],"experimental":[226],"results":[227],"based":[228],"on":[229],"large-scale":[231],"sample":[232],"collections":[233],"from":[234],"anti-malware":[235],"industry":[236],"demonstrate":[237],"performance":[239],"comparison":[243],"state-of-the-art":[245],"baselines":[246],"popular":[248],"security":[250],"products.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
